This paper explores the distribution of educational resources from the perspective of public service equalization in China, with a particular focus on government responsibility and fiscal input. Initially, the paper reviews the theoretical foundations and empirical studies concerning the distribution of educational resources, analyzing the role of government in educational equity and the impact of fiscal expenditure. By employing quantitative analysis methods, this study utilizes data on provincial education expenditures over several years to examine the relationship between government fiscal input and the equalization of educational resources. Empirical results indicate that increasing educational fiscal input and optimizing the allocation mechanism significantly enhance the level of equalization in educational resources. Furthermore, through case analyses of several local governments, effective policy recommendations are proposed to promote the fair distribution and optimization of educational resources. Lastly, the paper discusses potential obstacles in policy implementation and suggests corresponding strategies.

High-quality development in China requires higher vocational education, scientific and technological innovation, and sustainable economic development. The spatial distribution patterns of these factors show higher levels in the east and coastal areas compared to the west and inland regions, emphasizing the need for coupling coordination with the social economy. This study examines the impact of sustainable economic development on the coupling coordination degree using the spatial Durbin model. The results show a positive promotion and spillover effect, with regional variations. The main factors affecting the difference in coupling coordination are the amount of technology market contracts, fiscal expenditure on science and technology, patent application authorizations, tertiary industry output value, and the number of R&D institutions. According to the grey prediction model, the coupling coordination degree is expected to increase from 2022 to 2025, but achieving primary coordination may still be challenging in some areas. Therefore, strategies that utilize regional characteristics for coordinated development should be developed to improve the level of coupling coordination and create a mutually beneficial environment.

Accurate temperature control during the induction heating process of carbon fiber reinforced polymer (CFRP) is crucial for the curing effect of the material. This paper first builds a finite element model of induction heating, which combines the actual fiber structure and resin matrix, and systematically analyzes the heating mechanism and temperature field distribution of CFRP during the heating process. Based on the temperature distribution and variation observed in the material heating process, a PID control method optimized by the sparrow search algorithm is proposed, which effectively reduces the temperature overshoot and improves the response speed. The experiment verifies the effectiveness of the algorithm in controlling the temperature of the CFRP plate during the induction heating process. This study provides an effective control strategy and research method to improve the accuracy of temperature control in the induction heating process of CFRP, which helps to improve the results in this field.

This study introduces a novel Groundwater Flooding Risk Assessment (GFRA) model to evaluate risks associated with groundwater flooding (GF), a globally significant hazard often overshadowed by surface water flooding. GFRA utilizes a conditional probability function considering critical factors, including topography, ground slope, and land use-recharge to generate a risk assessment map. Additionally, the study evaluates the return period of GF events (GFRP) by fitting annual maxima of groundwater levels to probability distribution functions (PDFs). Approximately 57% of the pilot area falls within high and critical GF risk categories, encompassing residential and recreational areas. Urban sectors in the north and east, containing private buildings, public centers, and industrial structures, exhibit high risk, while developing areas and agricultural lands show low to moderate risk. This serves as an early warning for urban development policies. The Generalized Extreme Value (GEV) distribution effectively captures groundwater level fluctuations. According to the GFRP model, about 21% of the area, predominantly in the city's northeast, has over 50% probability of GF exceedance (1 to 2-year return period). Urban outskirts show higher return values (> 10 years). The model's predictions align with recorded flood events (90% correspondence). This approach offers valuable insights into GF threats for vulnerable locations and aids proactive planning and management to enhance urban resilience and sustainability.

In today’s digital education landscape, safeguarding the privacy and security of educational data, particularly the distribution of grades, is paramount. This research presents the “secure grade distribution scheme (SGDS)”, a comprehensive solution designed to address critical aspects of key management, encryption, secure communication, and data privacy. The scheme’s heart lies in its careful key management strategy, offering a structured approach to key generation, rotation, and secure storage. Hardware security modules (HSMs) are central to fortifying encryption keys and ensuring the highest security standards. The advanced encryption standard (AES) is employed to encrypt graded data, guaranteeing the confidentiality and integrity of information during transmission and storage. The scheme integrates the Diffie-Hellman key exchange protocol to establish secure communication, enabling users to securely exchange encryption keys without vulnerability to eavesdropping or interception. Secure communication channels further fortify graded data protection, ensuring data integrity in transit. The research findings underscore the SGDS’s efficacy in achieving the goals of secure grade distribution and data privacy. The scheme provides a holistic approach to safeguarding educational data, ensuring the confidentiality of sensitive information, and protecting against unauthorized access. Future research opportunities may centre on enhancing the scheme’s robustness and scalability in diverse educational settings.